Activity analysis, fall detection and risk assessment systems and methods

摘要

Aspects of the present disclosure include methods and corresponding systems for performing health risk assessments for a patient in the home environment. In various aspects, depth image data for a person may be obtained and subsequently processed to generate one or more parameters, such as temporal and spatial gait parameters. Subsequently, the generated parameters may be processed with other medical information related to the patient, such as electronic health records, to perform various health risk assessments.

主权项

1. A method comprising:
receiving, by at least one processor, depth image data from at least one depth camera, wherein the depth image data comprises a plurality of frames that depict a person walking through a home environment over time, the frames comprising a plurality of pixels; performing, by the at least one processor, segmentation on the pixels of the frames; in response to the segmentation, (1) generating, by the at least one processor, a three-dimensional (3D) data object based on the depth image data, and (2) tracking, by the at least one processor, the 3D data object over a plurality of frames of the depth image data, wherein the tracked 3D data object comprises time-indexed spatial data that represents the person walking through the home environment over time; identifying, by the at least one processor, a walking sequence from the tracked 3D data object, wherein the identifying step comprises:
the at least one processor determining a speed for the tracked 3D data object over a time frame;the at least one processor comparing the determined speed with a speed threshold;in response to the comparison indicating that the determined speed is greater than the speed threshold, the at least one processor assigning a state indicative of walking to the tracked 3D data object;while the tracked 3D data object is in the assigned walking state:
the at least one processor determining a walk straightness for the tracked 3D data object;the at least one processor determining a walk length for the tracked 3D data object;the at least one processor determining a walk duration for the tracked 3D data object;the at least one processor saving the tracked 3D data object in memory as the identified walking sequence when (i) the determined walk straightness exceeds a straightness threshold, (ii) the determined walk length exceeds a walk length threshold, and (iii) the determined walk duration exceed a walk duration threshold;the at least one processor excluding from the identified walking sequence in the memory the time-indexed spatial data from the tracked 3D data object corresponding to a time period where the determined walk straightness is less than the walk straightness threshold;the at least one processor repeating the speed determining step and the comparing step for the tracked 3D data object while the tracked 3D data object is in the assigned walking state; andthe at least one processor assigning a state indicative of not walking to the tracked 3D data object in response to a determination that the speed of the tracked 3D data object in the walking state has fallen below the speed threshold; analyzing, by the at least one processor, the time-indexed spatial data from the identified walking sequence to generate one or more gait parameters; and performing, by the at least one processor, at least one health risk assessment based on the one or more gait parameters to determine a health risk assessment score for the person.